Abstract Gastric cancer is the third leading cause of cancer mortality worldwide, with over 720,000 individuals succumbing to this disease each year. Survival to this malignancy remains dismal: only 4% of patients with metastatic gastric cancer are alive 5 years after diagnosis. Interestingly, recent gastric cancer genomic studies have shown that this malignancy is highly heterogeneous, with every tumor having hundreds of mutations. It is not known, however, how these mutations are organized into gastric tumor subclonal cell populations. Understanding the subclonal organization of gastric tumors is important as such information will be essential to design optimal molecular testing methods that guide precision medicine. In the present study, we will investigate regional and temporal changes in gastric cancer clonality to understand the levels of intra-tumor heterogeneity and subclonal architecture, and to identify tumor subclones carrying driver mutations that can be targeted for therapy. Although subclonal architecture studies have not yet been carried out in gastric cancer, recent studies in other cancer types, such as lung and renal tumors, have produced interesting, yet contrasting results. While driver mutations tend to be present in most lung tumor subclones, multiple and younger subclones carrying different drivers are characteristic of renal tumors. Thus, while both lung and renal cancer show extensive intra-tumor heterogeneity, these results suggest that limited sampling (i.e. a single biopsy) may be appropriate for molecularly-guided therapies in lung cancer but that more extensive multiregional sampling and analyses will be required for molecular diagnostics in renal cancer. Here we aim to improve our understanding of gastric cancer clonality and its relevance for molecular diagnostics by performing multi- regional sequencing of 30 gastric cancer tumors and by evaluating the levels of histological and genetic similarities of matching tumors when they are implanted into immunosuppressed NSG mice. Our guiding hypothesis is that extensive intra-tumor heterogeneity in gastric cancers leads to complex patters of tumor clonal architecture. Our aims in the study are as follows: (1) To investigate gastric cancer clonal diversity using multiregional sequencing and (2) To assess histological and genomic similarities between primary cancers and tumors derived from patient-derived xenograft models. These experiments will be crucial to elucidate the patterns of gastric cancer clonal evolution and their impact and relevance in precision medicine. In particular, we will uncover the distribution of driver mutations in gastric cancer subclones and will provide a very strong basis to design further preclinical studies and clinical trials that efficiently target such mutations, leading to much needed improvements in gastric cancer survival. Our findings will be also relevant to address cancer disparities in the country as gastric cancer disproportionally affects U.S. Hispanics.